A strategy for greenhouse climate control, part I: Model development

This paper presents an algorithm developed to predict the dynamic ambient g reenhouse air conditions which optimize net profits for the production of a greenhouse tomato crop. Profits are equated to the crop yield value less t he energy costs for heating and dehumidification and the CO2 injection cost . The climatic conditions considered are CO2 level, temperature, relative h umidity and incident radiation. These are varied dynamically for every time interval spanning the harvesting period. The algorithm has two sub-programs. For sets of selected internal climatic parameters, the first calculates crop yield, and the second calculates ener gy costs (heating and dehumidification) with reference to predicted exterio r climatic conditions (solar radiation, temperature, wind velocity and rela tive humidity). These two algorithms are then used to predict the particula r set of climatic parameters, adjusted for each time interval over the harv esting period, that will maximize the crop yield value less the energy cost s. (C) 2001 Silsoe Research Institute.